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Zhu W, Pan L, Cui X, Russo AC, Ray R, Pederson B, Wei X, Lin LL, Hafner H, Gregg B, Shrestha N, Liu C, Naji A, Arvan P, Sandoval DA, Lindberg I, Qi L, Reinert RB. SEL1L-HRD1 ER-Associated Degradation Facilitates Prohormone Convertase 2 Maturation and Glucagon Production in Islet α Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.20.644437. [PMID: 40166183 PMCID: PMC11957139 DOI: 10.1101/2025.03.20.644437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Proteolytic cleavage of proglucagon by prohormone convertase 2 (PC2) is required for islet α cells to generate glucagon. However, the regulatory mechanisms underlying this process remain largely unclear. Here, we report that SEL1L-HRD1 endoplasmic reticulum (ER)-associated degradation (ERAD), a highly conserved protein quality control system responsible for clearing misfolded proteins from the ER, plays a key role in glucagon production by regulating turnover of the nascent proform of the PC2 enzyme (proPC2). Using a mouse model with SEL1L deletion in proglucagon-expressing cells, we observed a progressive decline in stimulated glucagon secretion and a reduction in pancreatic glucagon content. Mechanistically, we found that endogenous proPC2 is a substrate of SEL1L-HRD1 ERAD, and that degradation of misfolded proPC2 ensures the maturation of activation-competent proPC2 protein. These findings identify ERAD as a novel regulator of PC2 biology and an essential mechanism for maintaining α cell function.
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Affiliation(s)
- Wenzhen Zhu
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Linxiu Pan
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
- Present address: Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Xianwei Cui
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Anna Chiara Russo
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Rohit Ray
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Brent Pederson
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Xiaoqiong Wei
- Present address: Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Liangguang Leo Lin
- Present address: Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Hannah Hafner
- Department of Pediatrics, Division of Pediatric Endocrinology, University of Michigan, Ann Arbor, MI 48105, USA
| | - Brigid Gregg
- Department of Pediatrics, Division of Pediatric Endocrinology, University of Michigan, Ann Arbor, MI 48105, USA
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA
| | - Neha Shrestha
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Chengyang Liu
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ali Naji
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Peter Arvan
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Darleen A. Sandoval
- Department of Surgery, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pediatrics, Nutrition Section, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Iris Lindberg
- Department of Anatomy and Neurobiology, University of Maryland-Baltimore, Baltimore, MD 21201, USA
| | - Ling Qi
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
- Present address: Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
- Department of Molecular & Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48105, USA
| | - Rachel B. Reinert
- Division of Metabolism, Endocrinology & Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48105, USA
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Oh J, Cha J, Choi S. Identification of Novel Genetic Variants and Food Intake Factors Associated with Type 2 Diabetes in South Korean Adults, Using an Illness-Death Model. Int J Mol Sci 2025; 26:2597. [PMID: 40141237 PMCID: PMC11942363 DOI: 10.3390/ijms26062597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2025] [Revised: 03/09/2025] [Accepted: 03/11/2025] [Indexed: 03/28/2025] Open
Abstract
Type 2 diabetes (T2D) is a prevalent chronic disease in the Korean population, influenced by lifestyle, dietary habits, and genetics. This study aimed to identify the effects of food intake and genetic factors on T2D progression in Korean adults using a multi-state illness-death model. We analyzed three transition models: normal glucose tolerance (NGT) to prediabetes (PD), NGT to T2D, and PD to T2D. We first identified dietary patterns significantly associated with each transition, using multivariate Cox proportional hazards models. Then, we assessed the impact of single-nucleotide polymorphisms (SNPs) on each transition, incorporating these dietary patterns as covariates. Our analysis revealed significant associations between the identified dietary patterns and the risk of PD and T2D incidence among individuals with NGT. We also identified novel genetic variants associated with disease progression: two SNPs (rs4607517 in Glucokinase [GCK] and rs758982 in Calcium/Calmodulin-Dependent Protein Kinase II Beta [CAMK2B]) in the NGT to PD model, and eight SNPs in the NGT to T2D model, including variants in the Zinc Finger Protein 106 (ZNF106), PTOV1 Extended AT-Hook Containing Adaptor Protein (PTOV1), Proprotein Convertase Subtilisin/Kexin Type 2 (PCSK2), Forkhead Box D2 (FOXD2), Solute Carrier Family 38 Member 7 (SLC38A7), and Neuronal Growth Regulator 1 (NEGR1) genes. Functional annotation analysis using ANNOVAR revealed that rs4607517 (GCK) and rs59595912 (PTOV1) exhibited high Combined Annotation-Dependent Depletion (CADD) and Deleterious Annotation of Genetic Variants using Neural Networks (DANN) scores, suggesting potential pathogenicity and providing a functional basis for their association with T2D progression. Integrating dietary and genetic factors with a multi-state model, this comprehensive approach offers valuable insights into T2D development and highlights potential targets for prevention and personalized interventions.
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Affiliation(s)
- Jeongmin Oh
- Department of Applied Mathematics, College of Science and Convergence Technology, Hanyang University, 55 Hanyang-daehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea;
| | - Junho Cha
- Department of Applied Artificial Intelligence, College of Computing, Hanyang University, 55 Hanyang-daehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea;
| | - Sungkyoung Choi
- Department of Applied Mathematics, College of Science and Convergence Technology, Hanyang University, 55 Hanyang-daehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea;
- Department of Applied Artificial Intelligence, College of Computing, Hanyang University, 55 Hanyang-daehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea;
- Department of Mathematical Data Science, College of Science and Convergence Technology, Hanyang University, 55 Hanyang-daehak-ro, Sangnok-gu, Ansan 15588, Republic of Korea
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3
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Ma ZW, Mou JY, Yuan Q, Wang ZY, Liu QH, Deng B, Zhang YD, Tang DQ, Wang L. Molecular exploration of the diurnal alteration of glycogen structural fragility and stability in time-restricted-feeding mouse liver. Int J Biol Macromol 2024; 277:134225. [PMID: 39074710 DOI: 10.1016/j.ijbiomac.2024.134225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 07/23/2024] [Accepted: 07/26/2024] [Indexed: 07/31/2024]
Abstract
The structure of glycogen α particles in healthy mouse liver has two states: stability and fragility. In contrast, glycogen α particles in diabetic liver present consistent fragility, which may exacerbate hyperglycemia. Currently, the molecular mechanism behind glycogen structural alteration is still unclear. In this study, we characterized the fine molecular structure of liver glycogen α particles in healthy mice under time-restricted feeding (TRF) mode during a 24-h cycle. Then, differentially expressed genes (DEGs) in the liver during daytime and nighttime were revealed via transcriptomics, which identified that the key downregulated DEGs were mainly related to insulin secretion in daytime. Furthermore, GO annotation and KEGG pathway enrichment found that negative regulation of the glycogen catabolic process and insulin secretion process were significantly downregulated in the daytime. Therefore, transcriptomic analyses indicated that the structural stability of glycogen α particles might be correlated with the glycogen degradation process via insulin secretion downregulation. Further molecular experiments confirmed the significant upregulation of glycogen phosphorylase (PYGL), phosphorylated PYGL (p-PYGL), and glycogen debranching enzyme (AGL) at the protein level during the daytime. Overall, we concluded that the downregulation of insulin secretion in the daytime under TRF mode facilitated glycogenolysis, contributing to the structural stability of glycogen α-particles.
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Affiliation(s)
- Zhang-Wen Ma
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, China; Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China; State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, Macau SAR, China
| | - Jing-Yi Mou
- Department of Clinical Medicine, School of The First Clinical Medicine, Xuzhou Medical University, Xuzhou, China; Department of Thyroid and Breast Surgery, Affiliated Hospital of Xuzhou Medical University, Xuzhou, China; Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Quan Yuan
- Department of Intelligent Medical Engineering, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Zi-Yi Wang
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia
| | - Qing-Hua Liu
- State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, Macau SAR, China
| | - Bin Deng
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yu-Dong Zhang
- Department of Clinical Medicine, School of The First Clinical Medicine, Xuzhou Medical University, Xuzhou, China.
| | - Dao-Quan Tang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, China.
| | - Liang Wang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, China; Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China; School of Agriculture and Food Sciences, The University of Queensland, Brisbane, Queensland, Australia; Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia 6027, Australia.
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Ruggiero-Ruff RE, Le BH, Villa PA, Lainez NM, Athul SW, Das P, Ellsworth BS, Coss D. Single-Cell Transcriptomics Identifies Pituitary Gland Changes in Diet-Induced Obesity in Male Mice. Endocrinology 2024; 165:bqad196. [PMID: 38146776 PMCID: PMC10791142 DOI: 10.1210/endocr/bqad196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/15/2023] [Accepted: 12/22/2023] [Indexed: 12/27/2023]
Abstract
Obesity is a chronic disease with increasing prevalence worldwide. Obesity leads to an increased risk of heart disease, stroke, and diabetes, as well as endocrine alterations, reproductive disorders, changes in basal metabolism, and stress hormone production, all of which are regulated by the pituitary. In this study, we performed single-cell RNA sequencing of pituitary glands from male mice fed control and high-fat diet (HFD) to determine obesity-mediated changes in pituitary cell populations and gene expression. We determined that HFD exposure is associated with dramatic changes in somatotrope and lactotrope populations, by increasing the proportion of somatotropes and decreasing the proportion of lactotropes. Fractions of other hormone-producing cell populations remained unaffected. Gene expression changes demonstrated that in HFD, somatotropes became more metabolically active, with increased expression of genes associated with cellular respiration, and downregulation of genes and pathways associated with cholesterol biosynthesis. Despite a lack of changes in gonadotrope fraction, genes important in the regulation of gonadotropin hormone production were significantly downregulated. Corticotropes and thyrotropes were the least affected in HFD, while melanotropes exhibited reduced proportion. Lastly, we determined that changes in plasticity and gene expression were associated with changes in hormone levels. Serum prolactin was decreased corresponding to reduced lactotrope fraction, while lower luteinizing hormone and follicle-stimulating hormone in the serum corresponded to a decrease in transcription and translation. Taken together, our study highlights diet-mediated changes in pituitary gland populations and gene expression that play a role in altered hormone levels in obesity.
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Affiliation(s)
- Rebecca E Ruggiero-Ruff
- Division of Biomedical Sciences; School of Medicine, University of California, Riverside, CA 92521, USA
| | - Brandon H Le
- Institute for Integrative Genome Biology Bioinformatics Core Facility, University of California, Riverside, CA 92521, USA
| | - Pedro A Villa
- Division of Biomedical Sciences; School of Medicine, University of California, Riverside, CA 92521, USA
| | - Nancy M Lainez
- Division of Biomedical Sciences; School of Medicine, University of California, Riverside, CA 92521, USA
| | - Sandria W Athul
- Department of Physiology, School of Medicine, Southern Illinois University, Carbondale, IL 62901, USA
| | - Pratyusa Das
- Department of Physiology, School of Medicine, Southern Illinois University, Carbondale, IL 62901, USA
| | - Buffy S Ellsworth
- Department of Physiology, School of Medicine, Southern Illinois University, Carbondale, IL 62901, USA
| | - Djurdjica Coss
- Division of Biomedical Sciences; School of Medicine, University of California, Riverside, CA 92521, USA
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5
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Bauer BM, Bhattacharya S, Bloom-Saldana E, Irimia-Dominguez JM, Fueger PT. Dose-dependent progression of multiple low-dose streptozotocin-induced diabetes in mice. Physiol Genomics 2023; 55:381-391. [PMID: 37458461 PMCID: PMC10642924 DOI: 10.1152/physiolgenomics.00032.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/17/2023] [Accepted: 06/30/2023] [Indexed: 07/28/2023] Open
Abstract
This study investigated the effects of different multiple low doses of streptozotocin (STZ), namely 35 and 55 mg/kg, on the onset and progression of diabetes in mice. Both doses are commonly used in research, and although both induced a loss of beta cell mass, they had distinct effects on whole glucose tolerance, beta cell function, and gene transcription. Mice treated with 55 mg/kg became rapidly glucose intolerant, whereas those treated with 35 mg/kg had a slower onset and remained glucose tolerant for up to a week before becoming equally glucose intolerant as the 55 mg/kg group. Beta cell mass loss was similar between the two groups, but the 35 mg/kg-treated mice had improved glucose-stimulated insulin secretion in gold-standard hyperglycemic clamp studies. Transcriptomic analysis revealed that the 55 mg/kg dose caused disruptions in nearly five times as many genes as the 35 mg/kg dose in isolated pancreatic islets. Pathways that were downregulated in both doses were more downregulated in the 55 mg/kg-treated mice, whereas pathways that were upregulated in both doses were more upregulated in the 35 mg/kg-treated mice. Moreover, we observed a differential downregulation in the 55 mg/kg-treated islets of beta cell characteristic pathways, such as exocytosis or hormone secretion. On the other hand, apoptosis was differentially upregulated in 35 mg/kg-treated islets, suggesting different transcriptional mechanisms in the onset of STZ-induced damage in the islets. This study demonstrates that the two STZ doses induce distinctly mechanistic progressions for the loss of functional beta cell mass.
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Affiliation(s)
- Brandon M Bauer
- Department of Molecular & Cellular Endocrinology, Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, California, United States
- Irell & Manella Graduate School of Biological Science, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Supriyo Bhattacharya
- Integrative Genomics Core, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Elizabeth Bloom-Saldana
- Department of Molecular & Cellular Endocrinology, Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, California, United States
- Comprehensive Metabolic Phenotyping Core, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Jose M Irimia-Dominguez
- Department of Molecular & Cellular Endocrinology, Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, California, United States
- Comprehensive Metabolic Phenotyping Core, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Patrick T Fueger
- Department of Molecular & Cellular Endocrinology, Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, California, United States
- Comprehensive Metabolic Phenotyping Core, Beckman Research Institute, City of Hope, Duarte, California, United States
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Basu J, Mukherjee R, Sahu P, Datta C, Chowdhury S, Mandal D, Ghosh A. Association of common variants of TCF7L2 and PCSK2 with gestational diabetes mellitus in West Bengal, India. NUCLEOSIDES, NUCLEOTIDES & NUCLEIC ACIDS 2023; 43:185-202. [PMID: 37610142 DOI: 10.1080/15257770.2023.2248201] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 08/07/2023] [Accepted: 08/09/2023] [Indexed: 08/24/2023]
Abstract
The genetic etiology of gestational diabetes mellitus (GDM) was suggested to overlap with type-2 diabetes(T2D). Transcription factor 7-like 2 (TCF7L2) and Proprotein Convertase Subtilisin/Kexin type 2 (PCSK2) are T2D susceptibility genes of the insulin synthesis/processing pathway. We analyzed associations of TCF7L2 and PCSK2 variants with GDM risk and evaluated their potential impact on impaired insulin processing in an eastern Indian population. The study included 114 GDM (case) and 228 non-GDM pregnant women (control). rs7903146, rs4132670, rs12255372 of TCF7L2, and rs2269023 of PCSK2 were genotyped by PCR-RFLP, and genotype distributions were compared between case and control. Fasting serum proinsulin and C-peptide levels were measured by ELISA and the Proinsulin/C-peptide ratio was considered an indicator of proinsulin conversion. Significantly higher frequency of risk allele (T) of rs12255372 (p = 0.02, OR = 2.0, 95%CI = 1.11-3.64) and rs4132670 (p = 0.002, OR = 2.26, 95%CI = 1.32-3.87) of TCF7L2 was found in GDM cases than non-GDM controls; TT genotype was associated with significantly increased disease risk. In rs7903146 (TCF7L2) and rs2269023 (PCSK2), although the frequency of risk allele (T) was not significantly higher in cases than controls, an association of TT for both variants remained significant with higher GDM risk in the recessive model. Increased serum pro-insulin and proinsulin:c-peptide ratio was found in GDM than non-GDM women and the phenomenon showed significant association with careers of risk alleles for TCF7L2 variants. In conclusion, TCF7L2 and PCSK2 variants are related to GDM risk in the studied population and hence may serve as potential biomarkers for assessing the disease risk. TCF7L2 variants contribute to impaired insulin processing.
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Affiliation(s)
- Jayita Basu
- Department of Life Sciences, Presidency University, Kolkata, India
| | | | - Pooja Sahu
- Department of Gynecology and Obstetrics, Institute of Post Graduate Medical Education and Research, Kolkata, India
| | - Chhanda Datta
- Department of Pathology, Institute of Post Graduate Medical Education and Research, Kolkata, India
| | - Subhankar Chowdhury
- Department of Endocrinology, Institute of Post Graduate Medical Education and Research, Kolkata, India
| | - Debasmita Mandal
- Department of Gynecology and Obstetrics, Institute of Post Graduate Medical Education and Research, Kolkata, India
| | - Amlan Ghosh
- Department of Life Sciences, Presidency University, Kolkata, India
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7
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Bayer S, Reik A, von Hesler L, Hauner H, Holzapfel C. Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review. Nutrients 2023; 15:nu15071695. [PMID: 37049537 PMCID: PMC10096950 DOI: 10.3390/nu15071695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/21/2023] [Accepted: 03/22/2023] [Indexed: 04/03/2023] Open
Abstract
The inter-individual variability of metabolic response to foods may be partly due to genetic variation. This systematic review aims to assess the associations between genetic variants and glucose response to an oral glucose tolerance test (OGTT). Three databases (PubMed, Web of Science, Embase) were searched for keywords in the field of genetics, OGTT, and metabolic response (PROSPERO: CRD42021231203). Inclusion criteria were available data on single nucleotide polymorphisms (SNPs) and glucose area under the curve (gAUC) in a healthy study cohort. In total, 33,219 records were identified, of which 139 reports met the inclusion criteria. This narrative synthesis focused on 49 reports describing gene loci for which several reports were available. An association between SNPs and the gAUC was described for 13 gene loci with 53 different SNPs. Three gene loci were mostly investigated: transcription factor 7 like 2 (TCF7L2), peroxisome proliferator-activated receptor gamma (PPARγ), and potassium inwardly rectifying channel subfamily J member 11 (KCNJ11). In most reports, the associations were not significant or single findings were not replicated. No robust evidence for an association between SNPs and gAUC after an OGTT in healthy persons was found across the identified studies. Future studies should investigate the effect of polygenic risk scores on postprandial glucose levels.
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Affiliation(s)
- Sandra Bayer
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Anna Reik
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Lena von Hesler
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
| | - Hans Hauner
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
- Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Christina Holzapfel
- Institute for Nutritional Medicine, School of Medicine, University Hospital “Klinikum Rechts der Isar”, Technical University of Munich, 80992 Munich, Germany
- Department of Nutritional, Food and Consumer Sciences, Fulda University of Applied Sciences, 36037 Fulda, Germany
- Correspondence:
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8
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Alur V, Raju V, Vastrad B, Vastrad C, Kavatagimath S, Kotturshetti S. Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus. Clin Med Insights Endocrinol Diabetes 2023; 16:11795514231155635. [PMID: 36844983 PMCID: PMC9944228 DOI: 10.1177/11795514231155635] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 01/19/2023] [Indexed: 02/23/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM. Methods The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes. Results A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes. Conclusion The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.
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Affiliation(s)
- Varun Alur
- Department of Endocrinology, J.J.M
Medical College, Davanagere, Karnataka, India
| | - Varshita Raju
- Department of Obstetrics and
Gynecology, J.J.M Medical College, Davanagere, Karnataka, India
| | - Basavaraj Vastrad
- Department of Pharmaceutical Chemistry,
K.L.E. College of Pharmacy, Gadag, Karnataka, India
| | | | - Satish Kavatagimath
- Department of Pharmacognosy, K.L.E.
College of Pharmacy, Belagavi, Karnataka, India
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9
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Broadaway KA, Yin X, Williamson A, Parsons VA, Wilson EP, Moxley AH, Vadlamudi S, Varshney A, Jackson AU, Ahuja V, Bornstein SR, Corbin LJ, Delgado GE, Dwivedi OP, Fernandes Silva L, Frayling TM, Grallert H, Gustafsson S, Hakaste L, Hammar U, Herder C, Herrmann S, Højlund K, Hughes DA, Kleber ME, Lindgren CM, Liu CT, Luan J, Malmberg A, Moissl AP, Morris AP, Perakakis N, Peters A, Petrie JR, Roden M, Schwarz PEH, Sharma S, Silveira A, Strawbridge RJ, Tuomi T, Wood AR, Wu P, Zethelius B, Baldassarre D, Eriksson JG, Fall T, Florez JC, Fritsche A, Gigante B, Hamsten A, Kajantie E, Laakso M, Lahti J, Lawlor DA, Lind L, März W, Meigs JB, Sundström J, Timpson NJ, Wagner R, Walker M, Wareham NJ, Watkins H, Barroso I, O'Rahilly S, Grarup N, Parker SC, Boehnke M, Langenberg C, Wheeler E, Mohlke KL. Loci for insulin processing and secretion provide insight into type 2 diabetes risk. Am J Hum Genet 2023; 110:284-299. [PMID: 36693378 PMCID: PMC9943750 DOI: 10.1016/j.ajhg.2023.01.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 01/03/2023] [Indexed: 01/25/2023] Open
Abstract
Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.
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Affiliation(s)
- K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Xianyong Yin
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Victoria A Parsons
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Emma P Wilson
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Anne H Moxley
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | | | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Anne U Jackson
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Vasudha Ahuja
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Stefan R Bornstein
- Department of Internal Medicine, Metabolic and Vascular Medicine, MedicCal Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Laura J Corbin
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Om P Dwivedi
- University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | | | | | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Stefan Gustafsson
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Liisa Hakaste
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ulf Hammar
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Christian Herder
- German Center for Diabetes Research, Neuherberg, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sandra Herrmann
- Department of Internal Medicine, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany
| | | | - David A Hughes
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus E Kleber
- Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany; SYNLAB MVZ Humangenetik Mannheim, Mannheim, BW, Germany
| | - Cecilia M Lindgren
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK; Wellcome Trust Centre Human Genetics, University of Oxford, Oxford, UK; Broad Institute, Cambridge, MA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anni Malmberg
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Angela P Moissl
- Institute of Nutritional Sciences, Friedrich-Schiller-University, Jena, Germany; Competence Cluster for Nutrition and Cardiovascular Health, Halle-Jena-Leipzig, Germany; Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Nikolaos Perakakis
- Department of Internal Medicine, Metabolic and Vascular Medicine, MedicCal Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - John R Petrie
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Peter E H Schwarz
- Department of Internal Medicine, Prevention and Care of Diabetes, Medical Faculty Carl Gustav Carus, Dresden, Germany; Helmholtz Zentrum München, Paul Langerhans Institute Dresden, University Hospital and Faculty of Medicine, TU Dresden, Dresden, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Sapna Sharma
- German Center for Diabetes Research, Neuherberg, Germany; Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Chair of Food Chemistry and Molecular Sensory Science, Technische Universität München, Freising, Germany
| | - Angela Silveira
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden; Oxford Biomedical Research Centre, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Rona J Strawbridge
- Institute of Health and Wellbeing, Mental Health and Wellbeing, University of Glasgow, Glasgow, UK; Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Tiinamaija Tuomi
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland; Abdominal Center, Endocrinology, Helsinki University Hospital, Helsinki, Finland
| | - Andrew R Wood
- Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Björn Zethelius
- Department of Geriatrics, Uppsala University, Uppsala, Sweden
| | - Damiano Baldassarre
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy; Cardiovascular Prevention Area, Centro Cardiologico Monzino I.R.C.C.S., Milan, Italy
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Folkhälsan Research Centre, Helsinki, Finland; Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jose C Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andreas Fritsche
- Department of Internal Medicine, Diabetology, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Bruna Gigante
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anders Hamsten
- Department of Medicine Solna, Division of Cardiovascular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eero Kajantie
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland; PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland; Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway; Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Deborah A Lawlor
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Lars Lind
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Winfried März
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim, BW, Germany; Medical Faculty Mannheim, Heidelberg University, Mannheim, BW, Germany
| | - James B Meigs
- Department of Medicine, Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Johan Sundström
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Robert Wagner
- Department of Internal Medicine, Diabetology, Tübingen, Germany; Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany; German Center for Diabetes Research, Neuherberg, Germany
| | - Mark Walker
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Health Data Research UK, Gibbs Building, London, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Inês Barroso
- Exeter Centre of Excellence for Diabetes Research, Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Stephen O'Rahilly
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephen Cj Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Boehnke
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
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10
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Zheng X, Ma J, Long J, Wei Q, Ren W. The HIF1α polymorphism rs2301104 is associated with obesity and obesity-related cytokines in Han Chinese population. Acta Diabetol 2023; 60:285-292. [PMID: 36422747 DOI: 10.1007/s00592-022-02008-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 11/11/2022] [Indexed: 11/26/2022]
Abstract
AIMS To evaluate the association between genetic polymorphisms of HIF1α and obesity and obesity-related cytokines in the Han Chinese population. METHODS The study consisted of 160 subjects with obesity and 166 age- and gender-matched healthy controls. We genotyped three tag single nucleotide polymorphisms (SNPs) of HIF1α by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based genotyping technology. Plasma cytokine concentrations were determined on the Luminex platform. The genetic associations were analysed statistically. RESULTS Obese subjects had significant obesity-related metabolic abnormalities, including hyperglycaemia, insulin resistance, and abnormalities in blood lipids, liver enzymes, and uric acid levels. SNP analysis of HIF1α revealed that the allele and genotype frequencies of rs2301104 were significantly associated with obesity. Our results suggest that the minor allele C of rs2301104 might be a protective mutation of obesity, and CC/CG genotypes of rs2301104 could be protective genotype of obesity. We also found that subjects with CC/CG genotypes of rs2301104 had significantly lower levels of IL-6, TNF-α, IL-1β, IL-8, and IL-10 than subjects with GG genotypes. CONCLUSIONS This is the first study to report an association between HIF1α polymorphisms and obesity and obesity-related cytokines in a Han Chinese population. These results require replication in larger populations but suggest that HIF1α may play an important role in obesity development.
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Affiliation(s)
- Xiaoya Zheng
- Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, No.1 Friendship Road, Yuzhong District, Chongqing, 400016, China.
| | - Jiani Ma
- Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, No.1 Friendship Road, Yuzhong District, Chongqing, 400016, China
| | - Jian Long
- Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, No.1 Friendship Road, Yuzhong District, Chongqing, 400016, China
| | - Qiang Wei
- Prevention of Disease Department, Chongqing Jiulongpo District Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Wei Ren
- Department of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, No.1 Friendship Road, Yuzhong District, Chongqing, 400016, China
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11
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Suur BE, Chemaly M, Lindquist Liljeqvist M, Djordjevic D, Stenemo M, Bergman O, Karlöf E, Lengquist M, Odeberg J, Hurt-Camejo E, Eriksson P, Ketelhuth DF, Roy J, Hedin U, Nyberg M, Matic L. Therapeutic potential of the Proprotein Convertase Subtilisin/Kexin family in vascular disease. Front Pharmacol 2022; 13:988561. [PMID: 36188622 PMCID: PMC9520287 DOI: 10.3389/fphar.2022.988561] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Proprotein convertase subtilisin/kexins (PCSKs) constitute a family of nine related proteases: PCSK1-7, MBTPS1, and PCSK9. Apart from PCSK9, little is known about PCSKs in cardiovascular disease. Here, we aimed to investigate the expression landscape and druggability potential of the entire PCSK family for CVD. We applied an integrative approach, combining genetic, transcriptomic and proteomic data from three vascular biobanks comprising carotid atherosclerosis, thoracic and abdominal aneurysms, with patient clinical parameters and immunohistochemistry of vascular biopsies. Apart from PCSK4, all PCSK family members lie in genetic regions containing variants associated with human cardiovascular traits. Transcriptomic analyses revealed that FURIN, PCSK5, MBTPS1 were downregulated, while PCSK6/7 were upregulated in plaques vs. control arteries. In abdominal aneurysms, FURIN, PCSK5, PCSK7, MBTPS1 were downregulated, while PCSK6 was enriched in diseased media. In thoracic aneurysms, only FURIN was significantly upregulated. Network analyses of the upstream and downstream pathways related to PCSKs were performed on the omics data from vascular biopsies, revealing mechanistic relationships between this protein family and disease. Cell type correlation analyses and immunohistochemistry showed that PCSK transcripts and protein levels parallel each other, except for PCSK9 where transcript was not detected, while protein was abundant in vascular biopsies. Correlations to clinical parameters revealed a positive association between FURIN plaque levels and serum LDL, while PCSK6 was negatively associated with Hb. PCSK5/6/7 were all positively associated with adverse cardiovascular events. Our results show that PCSK6 is abundant in plaques and abdominal aneurysms, while FURIN upregulation is characteristic for thoracic aneurysms. PCSK9 protein, but not the transcript, was present in vascular lesions, suggesting its accumulation from circulation. Integrating our results lead to the development of a novel ‘molecular’ 5D framework. Here, we conducted the first integrative study of the proprotein convertase family in this context. Our results using this translational pipeline, revealed primarily PCSK6, followed by PCSK5, PCSK7 and FURIN, as proprotein convertases with the highest novel therapeutic potential.
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Affiliation(s)
- Bianca E. Suur
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Melody Chemaly
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | | | - Djordje Djordjevic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Global Research Technologies, Novo Nordisk A/S, Maaloev, Denmark
| | - Markus Stenemo
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Otto Bergman
- Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eva Karlöf
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Mariette Lengquist
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Jacob Odeberg
- Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Department of Proteomics, School of Biotechnology, Royal Institute of Technology, Stockholm, Sweden
| | - Eva Hurt-Camejo
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Biopharmaceutical R&D, AstraZeneca, Mölndal, Sweden
| | - Per Eriksson
- Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Daniel F.J. Ketelhuth
- Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Cardiovascular and Renal Research, University of Southern Denmark, Odense, Denmark
| | - Joy Roy
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Hedin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Michael Nyberg
- Global Drug Discovery, Novo Nordisk A/S, Maaloev, Denmark
| | - Ljubica Matic
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Ljubica Matic,
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12
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Reference Genes across Nine Brain Areas of Wild Type and Prader-Willi Syndrome Mice: Assessing Differences in Igfbp7, Pcsk1, Nhlh2 and Nlgn3 Expression. Int J Mol Sci 2022; 23:ijms23158729. [PMID: 35955861 PMCID: PMC9369261 DOI: 10.3390/ijms23158729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 08/01/2022] [Accepted: 08/02/2022] [Indexed: 11/18/2022] Open
Abstract
Prader−Willi syndrome (PWS) is a complex neurodevelopmental disorder caused by the deletion or inactivation of paternally expressed imprinted genes at the chromosomal region 15q11−q13. The PWS-critical region (PWScr) harbors tandemly repeated non-protein coding IPW-A exons hosting the intronic SNORD116 snoRNA gene array that is predominantly expressed in brain. Paternal deletion of PWScr is associated with key PWS symptoms in humans and growth retardation in mice (PWScr model). Dysregulation of the hypothalamic−pituitary axis (HPA) is thought to be causally involved in the PWS phenotype. Here we performed a comprehensive reverse transcription quantitative PCR (RT-qPCR) analysis across nine different brain regions of wild-type (WT) and PWScr mice to identify stably expressed reference genes. Four methods (Delta Ct, BestKeeper, Normfinder and Genorm) were applied to rank 11 selected reference gene candidates according to their expression stability. The resulting panel consists of the top three most stably expressed genes suitable for gene-expression profiling and comparative transcriptome analysis of WT and/or PWScr mouse brain regions. Using these reference genes, we revealed significant differences in the expression patterns of Igfbp7, Nlgn3 and three HPA associated genes: Pcsk1, Pcsk2 and Nhlh2 across investigated brain regions of wild-type and PWScr mice. Our results raise a reasonable doubt on the involvement of the Snord116 in posttranscriptional regulation of Nlgn3 and Nhlh2 genes. We provide a valuable tool for expression analysis of specific genes across different areas of the mouse brain and for comparative investigation of PWScr mouse models to discover and verify different regulatory pathways affecting this complex disorder.
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13
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Zhang Z, Yang W, Zhu T, Wang L, Zhao X, Zhao G, Qu L, Jia Y. Genetic Parameter Estimation and Whole Sequencing Analysis of the Genetic Architecture of Chicken Keel Bending. Front Genet 2022; 13:833132. [PMID: 35401685 PMCID: PMC8984200 DOI: 10.3389/fgene.2022.833132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/24/2022] [Indexed: 11/18/2022] Open
Abstract
Bone health is particularly important for high-yielding commercial layer chickens. The keel of poultry is an extension of the abdomen side of the sternum along the sagittal plane and is one of the most important bones. In this study, the keel phenotype of White Leghorns laying hen flocks showed significant individual differences. To clarify its genetic mechanism, we first estimated the heritability of keel bend (KB) in White Leghorn, recorded the production performance of the chicken flock, examined the blood biochemical indexes and bone quality in KB and keel normal (KN) chickens, and performed whole-genome pooled sequencing in KB and KN chickens. We then performed selection elimination analysis to determine the genomic regions that may affect the keel phenotypes. The results show that KB is a medium heritability trait. We found that cage height had a significant effect on the KB (p < 0.01). At 48 weeks, there were significant differences in the number of eggs, the number of normal eggs, and eggshell strength (p < 0.05). The content of parathyroid hormone was lower (p < 0.01) and that of calcitonin was higher (p < 0.01) in KB chickens than in KN chickens. The differences in bone mineral density, bone strength, and bone cortical thickness of the humerus and femur were extremely significant (p < 0.01), with all being lower in KB chickens than in KN chickens. In addition, the bones of KB chickens contained more fat organization. A total of 128 genes were identified in selective sweep regions. We identified 10 important candidate genes: ACP5, WNT1, NFIX, CNN1, CALR, FKBP11, TRAPPC5, MAP2K7, RELA, and ENSGALG00000047166. Among the significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways found, we identifed two bone-related pathways, one involving “osteoclast differentiation” and the other the “MAPK signaling pathway.” These results may help us better understand the molecular mechanism of bone traits in chickens and other birds and provide new insights for the genetic breeding of chickens.
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Affiliation(s)
- Zhihao Zhang
- Institute of Animal Sciences, Chinese Academy of Agricultural Science, Beijing, China
| | - Weifang Yang
- Beijing General Station of Animal Husbandry, Beijing, China
| | - Tao Zhu
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Liang Wang
- Beijing General Station of Animal Husbandry, Beijing, China
| | - Xiaoyu Zhao
- Hebei Dawu Poultry Breeding Co., Ltd., Hebei, China
| | | | - Lujiang Qu
- State Key Laboratory of Animal Nutrition, Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
- *Correspondence: Lujiang Qu, ; Yaxiong Jia,
| | - Yaxiong Jia
- Institute of Animal Sciences, Chinese Academy of Agricultural Science, Beijing, China
- *Correspondence: Lujiang Qu, ; Yaxiong Jia,
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14
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Xu J, Jin L, Chen J, Zhang R, Zhang H, Li Y, Peng D, Gu Y, Wheeler MB, Hu C. Common variants in genes involved in islet amyloid polypeptide (IAPP) processing and the degradation pathway are associated with T2DM risk: A Chinese population study. Diabetes Res Clin Pract 2022; 185:109235. [PMID: 35131375 DOI: 10.1016/j.diabres.2022.109235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 01/22/2022] [Accepted: 01/31/2022] [Indexed: 11/28/2022]
Abstract
AIM To explore the genetic effects of SLC30A8, IAPP, PCSK1, PCSK2, CPE, PAM and IDE, key genes involved in IAPP processing and degradation pathway on T2DM risk and metabolic traits in Chinese population. METHODS Common variants were genotyped in 10936 Chinese subjects by Asian Screening Array and Multi-Ethnic Global Array. Associations of SNPs with occurrences of T2DM and related traits were evaluated through logistic and multiple linear regression. Genetic risk score (GRS) model was constructed based on 6 T2DM-variants, and its relationship with T2DM and related traits was assessed. RESULTS SLC30A8-rs13266634, PCSK1-rs155980, PCSK2-rs6136035, CPE-rs532192464, PAM-rs7716941, and IDE-rs117929184 were the top SNPs significantly associated with T2DM after adjusting for age, sex, and BMI, associated with blood glucose level, insulin secretion, and insulin sensitivity (all FDR p < 0.05). GRS calculated based on the above SNPs was remarkably correlated with T2DM, blood glucose, and insulin secretion. Furthermore, there was a significant interaction between SLC30A8 and IAPP in patients with T2DM (P = 0.0083). CONCLUSION Our study showed that common variants in genes involved in IAPP processing and the degradation pathway were associated with T2DM in Chinese population. Subjects with high GRS exhibited poorer glucose metabolism and insulin secretion.
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Affiliation(s)
- Jie Xu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China; Department of Physiology, 1 King's College Circle, University of Toronto, Toronto, Ontario M5S4L5, Canada
| | - Li Jin
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Jie Chen
- Department of Clinical Laboratory, Shanghai Xuhui Central Hospital, Shanghai 200020, China
| | - Rong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Hong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Yangyang Li
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Danfeng Peng
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Yunjuan Gu
- Department of Endocrinology, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, Jiangsu 226001, China.
| | - Michael B Wheeler
- Department of Physiology, 1 King's College Circle, University of Toronto, Toronto, Ontario M5S4L5, Canada.
| | - Cheng Hu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Diseases, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China; Institute for Metabolic Disease, Fengxian Central Hospital Affiliated to Southern Medical University, Shanghai 201499, China.
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15
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Ramzy A, Kieffer TJ. Altered islet prohormone processing: A cause or consequence of diabetes? Physiol Rev 2021; 102:155-208. [PMID: 34280055 DOI: 10.1152/physrev.00008.2021] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Peptide hormones are first produced as larger precursor prohormones that require endoproteolytic cleavage to liberate the mature hormones. A structurally conserved but functionally distinct family of nine prohormone convertase enzymes (PCs) are responsible for cleavage of protein precursors of which PC1/3 and PC2 are known to be exclusive to neuroendocrine cells and responsible for prohormone cleavage. Differential expression of PCs within tissues define prohormone processing; whereas glucagon is the major product liberated from proglucagon via PC2 in pancreatic α-cells, proglucagon is preferentially processed by PC1/3 in intestinal L cells to produce glucagon-like peptides 1 and 2 (GLP-1, GLP-2). Beyond our understanding of processing of islet prohormones in healthy islets, there is convincing evidence that proinsulin, proIAPP, and proglucagon processing is altered during prediabetes and diabetes. There is predictive value of elevated circulating proinsulin or proinsulin : C-peptide ratio for progression to type 2 diabetes and elevated proinsulin or proinsulin : C-peptide is predictive for development of type 1 diabetes in at risk groups. After onset of diabetes, patients have elevated circulating proinsulin and proIAPP and proinsulin may be an autoantigen in type 1 diabetes. Further, preclinical studies reveal that α-cells have altered proglucagon processing during diabetes leading to increased GLP-1 production. We conclude that despite strong associative data, current evidence is inconclusive on the potential causal role of impaired prohormone processing in diabetes, and suggest that future work should focus on resolving the question of whether altered prohormone processing is a causal driver or merely a consequence of diabetes pathology.
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Affiliation(s)
- Adam Ramzy
- Laboratory of Molecular and Cellular Medicine, Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada
| | - Timothy J Kieffer
- Laboratory of Molecular and Cellular Medicine, Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada.,Department of Surgery, University of British Columbia, Vancouver, BC, Canada.,School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
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16
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Williams L, Layton T, Yang N, Feldmann M, Nanchahal J. Collagen VI as a driver and disease biomarker in human fibrosis. FEBS J 2021; 289:3603-3629. [PMID: 34109754 DOI: 10.1111/febs.16039] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/19/2021] [Accepted: 05/27/2021] [Indexed: 12/12/2022]
Abstract
Fibrosis of visceral organs such as the lungs, heart, kidneys and liver remains a major cause of morbidity and mortality and is also associated with many other disorders, including cancer and metabolic disease. In this review, we focus upon the microfibrillar collagen VI, which is present in the extracellular matrix (ECM) of most tissues. However, expression is elevated in numerous fibrotic conditions, such as idiopathic pulmonary disease (IPF), and chronic liver and kidney diseases. Collagen VI is composed of three subunits α1, α2 and α3, which can be replaced with alternate chains of α4, α5 or α6. The C-terminal globular domain (C5) of collagen VI α3 can be proteolytically cleaved to form a biologically active fragment termed endotrophin, which has been shown to actively drive fibrosis, inflammation and insulin resistance. Tissue biopsies have long been considered the gold standard for diagnosis and monitoring of progression of fibrotic disease. The identification of neoantigens from enzymatically processed collagen chains have revolutionised the biomarker field, allowing rapid diagnosis and evaluation of prognosis of numerous fibrotic conditions, as well as providing valuable clinical trial endpoint determinants. Collagen VI chain fragments such as endotrophin (PRO-C6), C6M and C6Mα3 are emerging as important biomarkers for fibrotic conditions.
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Affiliation(s)
- Lynn Williams
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Science, University of Oxford, UK
| | - Thomas Layton
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Science, University of Oxford, UK
| | - Nan Yang
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Science, University of Oxford, UK
| | - Marc Feldmann
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Science, University of Oxford, UK
| | - Jagdeep Nanchahal
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Science, University of Oxford, UK
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17
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Maligłówka M, Bułdak Ł, Okopień B, Bołdys A. The consequences of PCSK9 inhibition in selected tissues. POSTEP HIG MED DOSW 2021. [DOI: 10.5604/01.3001.0014.9127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is one of nine members of the proprotein
convertase family. These serine proteases play a pivotal role in the post-translational
modification of proteins and the activation of hormones, enzymes, transcription factors and
growth factors. As a result, they participate in many physiological processes like embryogenesis,
activity of central nervous system and lipid metabolism. Scientific studies show
that the family of convertases is also involved in the pathogenesis of viral and bacterial
infections, osteoporosis, hyperglycaemia, cardiovascular diseases, neurodegenerative disorders
and cancer. The inhibition of PCSK9 by two currently approved for use monoclonal
antibodies (alirocumab, evolocumab) slows down the degradation of low-density lipoprotein
cholesterol receptors (LDLRs). This leads to increased density of LDLRs on the surface
of hepatocytes, resulting in decreased level of low-density lipoprotein cholesterol (LDL-C)
in the bloodstream, which is connected with the reduction of cardiovascular risk. PCSK9 inhibitors (PCSK9i) were created for the patients who could not achieve appropriate level
of LDL-C using current statin and ezetimibe therapy. It seems that high therapeutic efficacy
of PCSK9i will make them more common in the clinical use. The pleiotropic effects
of previously mentioned lipid-lowering therapies were the reasons for literature review of
possible positive and negative effects of PCSK9 inhibition beyond cholesterol metabolism.
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Affiliation(s)
- Mateusz Maligłówka
- Katedra Farmakologii, Klinika Chorób Wewnętrznych i Farmakologii Klinicznej, Wydział Nauk Medycznych Śląskiego Uniwersytetu Medycznego w Katowicach
| | - Łukasz Bułdak
- Katedra Farmakologii, Klinika Chorób Wewnętrznych i Farmakologii Klinicznej, Wydział Nauk Medycznych Śląskiego Uniwersytetu Medycznego w Katowicach
| | - Bogusław Okopień
- Katedra Farmakologii, Klinika Chorób Wewnętrznych i Farmakologii Klinicznej, Wydział Nauk Medycznych Śląskiego Uniwersytetu Medycznego w Katowicach
| | - Aleksandra Bołdys
- Katedra Farmakologii, Klinika Chorób Wewnętrznych i Farmakologii Klinicznej, Wydział Nauk Medycznych Śląskiego Uniwersytetu Medycznego w Katowicach
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18
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Abstract
The kexin-like proprotein convertases perform the initial proteolytic cleavages that ultimately generate a variety of different mature peptide and proteins, ranging from brain neuropeptides to endocrine peptide hormones, to structural proteins, among others. In this review, we present a general introduction to proprotein convertase structure and biochemistry, followed by a comprehensive discussion of each member of the kexin-like subfamily of proprotein convertases. We summarize current knowledge of human proprotein convertase insufficiency syndromes, including genome-wide analyses of convertase polymorphisms, and compare these to convertase null and mutant mouse models. These mouse models have illuminated our understanding of the roles specific convertases play in human disease and have led to the identification of convertase-specific substrates; for example, the identification of procorin as a specific PACE4 substrate in the heart. We also discuss the limitations of mouse null models in interpreting human disease, such as differential precursor cleavage due to species-specific sequence differences, and the challenges presented by functional redundancy among convertases in attempting to assign specific cleavages and/or physiological roles. However, in most cases, knockout mouse models have added substantively both to our knowledge of diseases caused by human proprotein convertase insufficiency and to our appreciation of their normal physiological roles, as clearly seen in the case of the furin, proprotein convertase 1/3, and proprotein convertase 5/6 mouse models. The creation of more sophisticated mouse models with tissue- or temporally-restricted expression of specific convertases will improve our understanding of human proprotein convertase insufficiency and potentially provide support for the emerging concept of therapeutic inhibition of convertases.
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Affiliation(s)
- Manita Shakya
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Iris Lindberg
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, USA
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19
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Chang SY, DeVera C, Yang Z, Yang T, Song L, McDowell A, Xiong ZG, Simon R, Zhou A. Hippocampal changes in mice lacking an active prohormone convertase 2. Hippocampus 2020; 30:715-723. [PMID: 32057164 DOI: 10.1002/hipo.23195] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 12/27/2019] [Accepted: 01/25/2020] [Indexed: 11/08/2022]
Abstract
Prohormone convertase 2 (PC2) is essential for the biosynthesis of many neuropeptides, including several of them in hippocampus. In mouse brain, lacking an enzymatically active PC2 (PC2-null) causes accumulation of many neuropeptides in their precursor or intermediate forms. Little is known about how a PC2-null state may affect the function of the hippocampus. In this study, adult PC2-null mice and their wildtype (WT) littermates were subjected to three analyses to determine possible changes associated with PC2-null at physiological, behavioral, and molecular levels, respectively, under normal and stressed conditions. Electrophysiological recordings of hippocampal slices were performed to measure evoked field-excitatory postsynaptic potentials (EPSP), long-term potentiation (LTP), and paired-pulse facilitation (PPF). Morris water maze (MWM) testing was conducted to examine behavioral changes that are indicative of hippocampal integrity. Quantitative mass spectrometry analysis was used to determine changes in the hippocampal proteome in response to a focal cerebral ischemic insult. We found that there were no significant differences in the threshold of evoked EPSPs between PC2-null and WT animals. However, an increase in LTP in both triggering rate and amplitude was observed in PC2-null mice, suggesting that PC2 may be involved in regulating synaptic strength. The PPF, on the other hand, showed a decrease in PC2-null mice, suggesting a presynaptic mechanism. Consistent with changes in LTP, PC2-null mice displayed decreased latencies in finding the escape platform in the MWM test. Further, after distal focal cerebral ischemia, the hippocampal proteomes incurred changes in both WT and PC2-null mice, with a prominent change in proteins associated with neurotransmission, exocytosis, and transport processes seen in the PC2-null but not WT mice. Taken together, our results suggest that PC2 is involved in regulating hippocampal synaptic plasticity, learning, and memory behaviors, as well as the hippocampal response to stresses originating in other regions of the brain.
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Affiliation(s)
- Su-Youne Chang
- Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota.,Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota
| | - Christopher DeVera
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Zhihua Yang
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Tao Yang
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Lina Song
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Arthur McDowell
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Zhi-Gang Xiong
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - Roger Simon
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
| | - An Zhou
- Department of Neurobiology, Neuroscience Institute, Morehouse School of Medicine, Atlanta, Georgia
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20
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Chen YC, Taylor AJ, Verchere CB. Islet prohormone processing in health and disease. Diabetes Obes Metab 2018; 20 Suppl 2:64-76. [PMID: 30230179 DOI: 10.1111/dom.13401] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 05/30/2018] [Accepted: 05/30/2018] [Indexed: 12/15/2022]
Abstract
Biosynthesis of peptide hormones by pancreatic islet endocrine cells is a tightly orchestrated process that is critical for metabolic homeostasis. Like neuroendocrine peptides, insulin and other islet hormones are first synthesized as larger precursor molecules that are processed to their mature secreted products through a series of proteolytic cleavages, mediated by the prohormone convertases Pc1/3 and Pc2, and carboxypeptidase E. Additional posttranslational modifications including C-terminal amidation of the β-cell peptide islet amyloid polypeptide (IAPP) by peptidyl-glycine α-amidating monooxygenase (Pam) may also occur. Genome-wide association studies (GWAS) have showed genetic linkage of these processing enzymes to obesity, β-cell dysfunction, and type 2 diabetes (T2D), pointing to their important roles in metabolism and blood glucose regulation. In both type 1 diabetes (T1D) and T2D, and in the face of metabolic or inflammatory stresses, islet prohormone processing may become impaired; indeed elevated proinsulin:insulin (PI:I) ratios are a hallmark of the β-cell dysfunction in T2D. Recent studies suggest that genetic or acquired defects in proIAPP processing may lead to the production and secretion of incompletely processed forms of proIAPP that could contribute to T2D pathogenesis, and additionally that impaired processing of both PI and proIAPP may be characteristic of β-cell dysfunction in T1D. In islet α-cells, the prohormone proglucagon is normally processed to bioactive glucagon by Pc2 but may express Pc1/3 under certain conditions leading to production of GLP-1(7-36NH2 ). A better understanding of how β-cell processing of PI and proIAPP, as well as α-cell processing of proglucagon, are impacted by genetic susceptibility and in the face of diabetogenic stresses, may lead to new therapeutic approaches for improving islet function in diabetes.
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Affiliation(s)
- Yi-Chun Chen
- Department of Surgery, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
| | - Austin J Taylor
- Department of Surgery, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
| | - C Bruce Verchere
- Department of Surgery, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, British Columbia, Canada
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21
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Winters A, Ramos-Molina B, Jarvela TS, Yerges-Armstrong L, Pollin TI, Lindberg I. Functional analysis of PCSK2 coding variants: A founder effect in the Old Order Amish population. Diabetes Res Clin Pract 2017; 131:82-90. [PMID: 28719828 PMCID: PMC5572827 DOI: 10.1016/j.diabres.2017.06.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 06/27/2017] [Accepted: 06/27/2017] [Indexed: 02/06/2023]
Abstract
AIMS In humans, noncoding variants of PCSK2, the gene encoding prohormone convertase 2 (PC2), have been previously associated with risk for and age of onset of type 2 diabetes (T2D). The aims of this study were to identify coding variants in PCSK2; to determine their possible association with glucose handling; and to determine functional outcomes for coding variants in biochemical studies. METHODS Exome-wide genotyping was performed on 1725 Old Order Amish (OOA) subjects. PCSK2 coding variants were tested for association with diabetes-related phenotypes. In vitro analyses using transfected human PC2-encoding constructs were performed to determine the impact of each mutation on PC2 activity. RESULTS We identified 10 rare missense coding variants in PCSK2 in various genomic databases. R430W (rs200711626) is greatly enriched in the OOA population (MAF 4.3%). This variant is almost twice as common (MAF 7.4%) in OOA individuals with T2D as in OOA individuals with normal or with normal/impaired glucose tolerance (MAF 3.9% and 2.9%, respectively; p=0.25 and p=0.10). In vitro experiments revealed a broadening of the pH optimum for the R430W variant, which may result in increased activity against PCSK2 substrates. CONCLUSIONS Although the association of the R430W variation with T2D in the OOA population did not reach significance, based upon the broadened pH profile of R430W PC2, we speculate that the presence of this substitution may result in altered processing of PCSK2 substrates, ultimately leading to increased conversion to diabetes.
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Affiliation(s)
- Alexandra Winters
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, United States; Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, United States
| | - Bruno Ramos-Molina
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, United States
| | - Timothy S Jarvela
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, United States
| | - Laura Yerges-Armstrong
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, United States
| | - Toni I Pollin
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, United States
| | - Iris Lindberg
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, United States.
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